A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Accelerated Variance Based Joint Sparsity Recovery of Images from Fourier Data
[article]
2019
arXiv
pre-print
Several problems in imaging acquire multiple measurement vectors (MMVs) of Fourier samples for the same underlying scene. Image recovery techniques from MMVs aim to exploit the joint sparsity across the measurements in the sparse domain. This is typically accomplished by extending the use of ℓ_1 regularization of the sparse domain in the single measurement vector (SMV) case to using ℓ_2,1 regularization so that the "jointness" can be accounted for. Although effective, the approach is inherently
arXiv:1910.08391v1
fatcat:vwfvsydhevgblfj6hfbipj2f2i